1. Field of the Invention
The invention relates generally to systems and methods for analysis of downhole data, and more particularly to systems and methods for identifying recurring patterns in data signals and using these patterns to reconstruct all or part of the data signals or to trigger functions that control operation of the well or pipeline.
2. Related Art
Downhole data from oil wells is often measured and analyzed in order to identify various conditions and characteristics associated with operation of the well. The measured data may, for example, consist of temperature measurements or pressure measurements.
Pressure measurements are commonly used to determine the rate of flow of fluid through wells or pipelines. For instance, pressure measurements can be made at two points on a pipeline and then a flow rate can be computed from the pressure drop across the distance between the pressure sensors. The computation of a flow rate based on pressure measurements is a relatively simple matter if the fluid in the pipeline is flowing slowly and is well-behaved, but the computation becomes more complex if the fluid is experiencing more complex flow.
The computation of fluid flow based on measured data may be affected, for example, by such things as the composition of the fluid (e.g., combinations of oil and water or gas and water) and turbulence or other flow structures (conditions that affect the character of fluid flow through the well). Some analysis may therefore be performed on the measured data in order to identify flow structures that affect the computations and determinations that are based on the measured data. Once these flow structures are identified, conditions such as flow rates can be more accurately determined. It may also be desirable to identify particular flow structures that can cause damage to the well, pipeline, associated equipment or even the oil-producing structures.
Identifying flow structures in a well or pipeline may be difficult for a number of reasons. For instance, data may be taken at irregular intervals, there may be gaps in the data, or the data may be noisy, so any analyses of the data may be inaccurate. Further, conventional analyses typically focus on the identification of sinusoidal signal components and typically are not able to distinguish non-sinusoidal patterns that are associated with flow structures that may be present. It would therefore be desirable to provide systems and methods that overcome one or more of these problems.